Should “Success” in Science Be Measured Differently?
Citations are valuable, but they don’t reflect the full scope of scientific contributions that are needed in research.
The growing competition for research funding and academic positions is one of the most central pressures in science today. In many top research countries, the success of a scientist—and thus, their suitability for securing funding or a promotion—is strongly tied to the volume of their research output. The number of publications they have and the impact factor of the journals they have appeared in are often used as a proxy for measuring career success.
This has given rise to a “publish or perish” culture within science. But this culture doesn’t just affect a scientist’s career, it could be affecting science itself. Analyses have found that this pressure to publish may introduce more bias in research and negatively impact the perceived trustworthiness of science. Surveys of scientists have also indicated that the “publish or perish” mindset could be contributing to the reproducibility crisis seen in biomedical research, as more than 60% of respondents to a recent PloS Biology study attributed irreproducibility issues to this pressure to prioritize quantity over quality.
Technology Networks recently spoke with a variety of academics at different stages of their careers, as well as several scientists working in industry, and asked them all, in the context of the current “publish or perish” culture: “Should success in science be measured differently?”
Dr. Vivian Li. Senior group leader and assistant research director, the Francis Crick Institute
“Publications, citations, and grants are often used as proxies for scientific achievements. While these metrics are convenient and widely adopted, they do not account for structural and often subconscious disadvantages related to factors such as institutional prestige, ethnicity, or career breaks (e.g., parenthood). Motherhood, in particular, can carry lasting and often invisible challenges, including reduced ability to travel or attend conferences, which can limit networking and career progression opportunities. Despite initiatives such as the San Francisco Declaration on Research Assessment (DORA), research assessment continues to be heavily influenced by journal-based metrics.
“To enable a more meaningful evaluation of scientific contribution, the reliance on impact factors should be reconsidered. Alternative approaches could include simpler journal-level indicators that prioritize rigor and reliability over perceived impact, alongside a shift towards open science practices such as preprints and transparent peer review, rather than a system centered on journal prestige.”
Dr. Xiang Ding. Research associate and core technology translator, University of Bath
“I think it should be measured more broadly. Publications and grants are important, but they are not the whole picture. Good science also includes rigor, reproducibility, mentorship, collaboration, openness, and real-world impact. Some of the most valuable scientific contributions are not always the fastest to publish or the easiest to quantify.
“I also think success should include how well researchers train others, share knowledge across disciplines, and help translate research into practical outcomes.” — Dr. Xiang Ding.
“In applied fields, especially, meaningful progress can involve long-term development, troubleshooting, and collaboration with many different people, and those contributions are not always captured well by simple metrics.”
Dr. Tammer Farid. General manager, Data, Champions Oncology
“The main limitation of our publication-driven research system is that so much excellent science doesn’t yield positive, publishable results. As a society, we lose the rigor of peer review to assess the quality of the work yielding non-results, and therefore other researchers tackling the same questions cannot easily benefit from that effort and may repeat it.”
Dr. Raeka Aiyar. Executive director, Institute for Glial Sciences, Case Western Reserve University
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“The metrics we use in science perpetuate the lone wolf and marginalize talent and innovation. Plenty of brilliant and promising scientists don't get the top grants in the field because there aren't enough grants to reward the talent out there.
“We need to broaden our images of what a successful scientist looks like, of who is really making an impact on the field.” — Dr. Raeka Aiyar.
“It's not only the scientist who went to Stanford, published a two-author Nature paper, and never sets foot outside of their field. It's also the scientist who overcame incredible personal challenges to pursue the project of their dreams, the scientist who built international collaborations and bridged disciplines, the scientist who did a stint in industry or pivoted to different fields throughout their career, the scientist who advocated for policies that improved everyone's labs or whose mentorship created paths their trainees never would have had otherwise, or who launched an education program that brought more young talent into the field.
“Having a one-size-fits-all mentality is preposterous in evaluating data, and so should it be for evaluating success. Thinking out of the box is expected when we're in scientific inquiry, yet we so often remain inside the box when it comes to how we evaluate each other. We shoot ourselves in the foot when we stick to these incredibly reductive metrics of journal name, impact factor, and grant dollars, and it is imperative that we get better at looking beyond them so that we do not keep hemorrhaging the talent that actually drives science forward. Nearly all of the ways that we recognize and reward merit need to be overhauled.”
Prof. Mark Lewis. Chief executive officer, MyoMaker Bio. Professor of musculoskeletal biology at Loughborough University
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“It probably should be, although it’s not a straightforward problem to solve. I spent around 20 years managing and mentoring people in academia, and these questions about how we measure success come up all the time.
“Historically, science has been dominated by white men, and biases within the system still affect how success is measured and recognized. There is evidence, for example, that people who take career breaks, women, or researchers from different ethnic backgrounds often appear less ‘successful’ by conventional metrics.” — Prof. Mark Lewis.
“But those metrics don’t account for different life circumstances. Someone who has worked full-time for 30 years will inevitably have a different publication and grant record from someone who has worked part-time over the same period because they’ve raised children, taken career breaks, or dealt with health issues such as cancer treatment.
Performance management in academia is a relatively recent development, introduced as higher education funding mechanisms changed. The current system is far from ideal, but the real challenge is identifying what should replace it. That’s a much harder question.”
Dr. Amos Chungwon Lee. Chief executive officer and co-founder, Meteor Biotech
“While publications and peer review remain essential pillars of the scientific method, they should not be the ultimate finish line. Science, by definition, is the study of our world to improve it. Therefore, success should not be measured merely by the perceived ‘prestige’ of a journal or the volume of publications, but by the true translational impact—how effectively a discovery transitions from the bench to real-world applications that improve human life.
“Currently, the citation system is flawed. It often creates academic echo chambers—or ‘silos’—where knowledge is only shared and cited within closed networks, heavily skewed toward whatever field is currently trending. We need to shift away from this popularity contest.
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“I believe the future of measuring scientific success lies in the integration of artificial intelligence. AI has the potential to objectively map the genealogy of ideas. Instead of relying on manual citation networks that are prone to human bias, AI can track, validate, and connect how foundational knowledge is formed and utilized across different disciplines over time. If we can use AI to trace the exact path from a piece of prior art to a real-world clinical application, we can finally reward researchers for their true contributions to society, regardless of the popularity of their specific subfield. Ultimately, success should be defined by real-world utility, and AI will be the tool that democratizes how we track and measure that impact.”
Annika Wittich. Scientific researcher, Fraunhofer Institute for Translational Medicine and Pharmacology
“I believe that publishing in highly cited journals alone does not fully reflect scientific success, and the criteria should be more diverse. For instance, sharing negative or inconclusive results is extremely valuable, as it helps other researchers avoid repeating the same dead ends and supports a more transparent research culture.
“Another dimension of successful science, which is important to me, is scientific education. Mentoring students and interns, and helping them develop critical thinking and research skills, is a lasting contribution that shapes the future of the scientific field. Finally, the translational impact of research is essential. Success should also reflect how well scientific work translates into real-world benefits, whether in improving healthcare, informing policy, or driving innovation.”
Dr. Alix Rouault. Senior scientist, Superluminal Medicines
“I agree that while publishing is essential for the scientific community to make informed decisions, it is not a definitive measure of merit. When success is measured primarily by paper output, it becomes easy to produce publishable work that does not actually advance science. For example, I have seen my own work replicated using a different species to reach the same conclusion, which adds little value to the field.
“Metrics like grant awards and citations are often flawed. Non-immigrant students on visas have fewer grant opportunities than citizens, and citation counts are frequently inflated by authors who repeatedly cite their own work.
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“I question whether measuring a scientist's success is even necessary. If asked whether a scientist is ‘good,’ my response would be: What is the question you are trying to answer?”
Dr. Joseph C. Wu. Director, Stanford Cardiovascular Institute. Professor of medicine and radiology, Stanford University
“Publications, citations, and grants remain important indicators of scientific rigor, but they do not fully capture the impact of modern biomedical research. Especially in fields like new approach methodologies (NAMs), success should also be measured by translational contribution, whether discoveries can be validated, reproduced, and implemented to improve predictive accuracy, regulatory decision-making, and ultimately patient outcomes.
“A more balanced framework that values real-world impact, reproducibility, and collaborative contributions, such as shared datasets, standardized protocols, and regulatory science, while enabling the development of therapeutic and preventive strategies, will better align scientific priorities with societal benefit. In this context, success is not only defined by what we publish, but by what we translate.”
Dr. Robert Schickel. Chief executive officer and co-founder, NUAgo Therapeutics
“Publications, citations, and grants remain important measures of scientific productivity, but they are not the ultimate purpose of science. The goal of research should be to generate knowledge that advances understanding and improves outcomes for society.
“I would like to see greater recognition of translational impact, scientific rigor, reproducibility, mentorship, and collaboration. Some of the most important scientific contributions influence future discovery and patient care in ways that cannot be fully captured through publication metrics alone.”
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